This invention relates to an object image detecting method in which an image of an object having features, such as a human face, is taken by a camera from an arbitrary direction and the image thus taken is matched to dictionary or library images previously generated and stored whereby a region of the object in the image is detected, and relates to a method of determining which category the object in the detected object region belongs to among predetermined categories such as human faces classified into corresponding categories and previously registered as well as detecting whether the object in the detected object region belongs to a predetermined category or not and also relates to a system using that method.
There may be a case where it is needed, for example, to automatically identify persons who wish to enter or exit from a particular room, buiding or area so that only predetermined particular persons such as employees or customers are to be permitted to enter or exit therefrom. Also, there may be a case where it is required to discriminate a doubtful or suspicious character or characters from among a great number of unspecified people who enter or exit from a bank or intend to do so. In such cases, it has been proposed to take pictures of people who enter or exit from a particular place or area or intend to do so by a camera and to identify or determine the faces of the people from the images thereof taken.
A prior art apparatus for extracting the object region in the image thereof is based on a thresholding of intensity and/or color information. For example, when a facial region of a person is extracted from the image thereof, intensity and/or saturation and/or hue corresponding to the skin are obtained to set a threshold for detecting the skin region thereby extracting the skin region from the whole image. Alternatively, there is a method of extracting the object region by modeling the shape of the object and fitting it with the edge of the image.
Another prior art object identifying apparatus is provided with a dictionary or library of facial images in a particular direction of a person or persons to be identified such as the direct frontal faces thereof, the side faces thereof or the like and matches a test image inputted thereinto to the facial images of the dictionary whereby the person is identified (see, for example, Ashoc Samal, Prasana A. Iyengar: "Automatic recognition and analysis of human faces and facial expressions" Pattern recognition, Vol. 25, No. 1, pp65-77, 1992).
The prior art object extracting apparatus using thresholding mentioned above is needed to set the optimum threshold. This optimum threshold may often vary with the direction or orientation of the object. Therefore, if the direction or orientation of the object is unknown, it is difficult to set the optimum threshold for extracting the object region. Also, the prior art method of fitting a modeled shape of the object with the edge of the image cannot extract the object region with high accuracy if the shape of the object in its image varies with the direction or orientation of the object, or the edge representing the contour or outline of the object cannot be extracted correctly from the image due to occlusion of a portion of the object or shadow of the object.
Further, the prior art object identifying apparatus is required to input the image (e.g., the direct frontal face) taken from the same direction as that from which the image prepared and stored in the dictionary is taken, and therefore has a limited scope to which the appratus is applied since it is necessary to limit the direction from which the object is taken by any procedure or means.